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Revista de la Sociedad Científica del Paraguay
versión impresa ISSN 0379-9123versión On-line ISSN 2617-4731
Resumen
JIMENEZ CHAVES, Viviana Elizabeth y TORRES, Miguel García. Analysis of Pre-school Education from Paraguay through Machine Learning Techniques. Rev. Soc. cient. Parag. [online]. 2019, vol.24, n.2, pp.293-304. ISSN 2617-4731. https://doi.org/10.32480/rscp.2019-24-2.293-304.
Pre-school education is the key to establish the knowledge base and skills that will be of vital importance in the future. In Paraguay, the Department od Statististics at the Ministry of Education and Science a collected data about the school enrolment of children throughout the contry. In this work a descriptive analysis is carried out using an unsupervised learning approach. For such purpose, the following vairables were selected: Department, year, sex, geographical area (rural or urban), sector (official, charter school or private) y level (first or second). Results achieved are promising and help to understand the current status of Paraguay regarding Pre-school education. The general conclusions of this works are, on one side, that EDM is an apporach that provides pwerfoul tools to analyse data in education. On the other hand, when including the context of needs and socio-economic reality of the country, the major cause of school dropout is the economic factor.
Palabras clave : Pre-school education; Paraguay; educational data mining.